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note: This error originates from a subprocess, and is likely not a problem with pip.
error: legacy-install-failure
Encountered error while trying to install package.
numpy
note: This is an issue with the package mentioned above, not pip.
hint: See above for output from the failure.
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
[notice] A new release of pip is available: 23.0.1 -> 23.1.2
[notice] To update, run: python.exe -m pip install --upgrade pip
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× pip subprocess to install build dependencies did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
[notice] A new release of pip is available: 23.0.1 -> 23.1.2
[notice] To update, run: python.exe -m pip install --upgrade pip
PyOD provides algorithms for modeling majority distribution of the data w/ un/semi-supervised algos between data points. To detect time series outliers, things like preprocess and signal extraction are needed. Otherwise, given a univariate time series data, only 1 feature is available for each data point w/ PyOD (which could be problematic). Also, detecting time series outlier is not just about modeling majority distribution of data points, some more things need to be considered (e.g., temporal dependency between data points, unusual temporal patterns). Those are the things that TODS is addressing.
It cannot be installed on Windows, cuz we are using a backbone package called D3M, which is not supporting systems other than Linux (not even M1+ OSX). We are finding a way to get rid of it now as it is not even able to support Python3.8+ as well.
it is written in
https://github.com/yzhao062/pyod
For time-series outlier detection, please use TODS. For graph outlier detection, please use PyGOD.
PyOD is the most comprehensive and scalable Python library for detecting outlying objects in multivariate data
may you clarify what is difference between TODS and pyod
by the way pyods can be installed on winodws 11 but tods not?
0\include\10.0.22000.0\shared -IC:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\winrt -IC:\Program Files (x86)\Windows Kits\10\include\10.0.22000.0\cppwinrt -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um /Tc_configtest.c /Fo_configtest.obj
error:
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× pip subprocess to install build dependencies did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
WARNING: Ignoring invalid distribution -orch (c:\my_py_environments\py310_env_apr2023\lib\site-packages)
[notice] A new release of pip is available: 23.0.1 -> 23.1.2
[notice] To update, run: python.exe -m pip install --upgrade pip
(py310_env_apr2023) C:\my_py_environments\py310_env_apr2023\Scripts>
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